You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
152 lines
5.9 KiB
152 lines
5.9 KiB
# -*- coding: utf-8 -*-
|
|
|
|
from nd2reader.model import Image, ImageSet
|
|
from nd2reader.parser import Nd2Parser
|
|
import six
|
|
|
|
|
|
class Nd2(Nd2Parser):
|
|
"""
|
|
Allows easy access to NIS Elements .nd2 image files.
|
|
|
|
"""
|
|
def __init__(self, filename):
|
|
super(Nd2, self).__init__(filename)
|
|
self._filename = filename
|
|
|
|
def __repr__(self):
|
|
return "\n".join(["<ND2 %s>" % self._filename,
|
|
"Created: %s" % self.absolute_start.strftime("%Y-%m-%d %H:%M:%S"),
|
|
"Image size: %sx%s (HxW)" % (self.height, self.width),
|
|
"Image cycles: %s" % len(self.time_indexes),
|
|
"Channels: %s" % ", ".join(["'%s'" % str(channel) for channel in self.channels]),
|
|
"Fields of View: %s" % len(self.fields_of_view),
|
|
"Z-Levels: %s" % len(self.z_levels)
|
|
])
|
|
|
|
def __len__(self):
|
|
"""
|
|
This should be the total number of images in the ND2, but it may be inaccurate. If the ND2 contains a
|
|
different number of images in a cycle (i.e. there are "gap" images) it will be higher than reality.
|
|
|
|
:rtype: int
|
|
|
|
"""
|
|
return self._total_images_per_channel * len(self.channels)
|
|
|
|
def __getitem__(self, item):
|
|
"""
|
|
Allows slicing ND2s.
|
|
|
|
>>> nd2 = Nd2("my_images.nd2")
|
|
>>> image = nd2[16] # gets 17th frame
|
|
>>> for image in nd2[100:200]: # iterate over the 100th to 200th images
|
|
>>> do_something(image.data)
|
|
>>> for image in nd2[::-1]: # iterate backwards
|
|
>>> do_something(image.data)
|
|
>>> for image in nd2[37:422:17]: # do something super weird if you really want to
|
|
>>> do_something(image.data)
|
|
|
|
:type item: int or slice
|
|
:rtype: nd2reader.model.Image() or generator
|
|
|
|
"""
|
|
if isinstance(item, int):
|
|
try:
|
|
channel_offset = item % len(self.channels)
|
|
fov = self._calculate_field_of_view(item)
|
|
channel = self._calculate_channel(item)
|
|
z_level = self._calculate_z_level(item)
|
|
image_group_number = int(item / len(self.channels))
|
|
timestamp, raw_image_data = self._get_raw_image_data(image_group_number, channel_offset)
|
|
image = Image(timestamp, raw_image_data, fov, channel, z_level, self.height, self.width)
|
|
except (TypeError, ValueError):
|
|
return None
|
|
except KeyError:
|
|
raise IndexError("Invalid frame number.")
|
|
else:
|
|
return image
|
|
elif isinstance(item, slice):
|
|
return self._slice(item.start, item.stop, item.step)
|
|
raise IndexError
|
|
|
|
def _slice(self, start, stop, step):
|
|
"""
|
|
Allows for iteration over a selection of the entire dataset.
|
|
|
|
:type start: int
|
|
:type stop: int
|
|
:type step: int
|
|
:rtype: nd2reader.model.Image() or None
|
|
|
|
"""
|
|
start = start if start is not None else 0
|
|
step = step if step is not None else 1
|
|
stop = stop if stop is not None else len(self)
|
|
# This weird thing with the step allows you to iterate backwards over the images
|
|
for i in range(start, stop)[::step]:
|
|
yield self[i]
|
|
|
|
@property
|
|
def image_sets(self):
|
|
"""
|
|
Iterates over groups of related images. This is useful if your ND2 contains multiple fields of view.
|
|
A typical use case might be that you have, say, four areas of interest that you're monitoring, and every
|
|
minute you take a bright field and GFP image of each one. For each cycle, this method would produce four
|
|
ImageSet objects, each containing one bright field and one GFP image.
|
|
|
|
:return: model.ImageSet()
|
|
|
|
"""
|
|
for time_index in self.time_indexes:
|
|
image_set = ImageSet()
|
|
for fov in self.fields_of_view:
|
|
for channel_name in self.channels:
|
|
for z_level in self.z_levels:
|
|
image = self.get_image(time_index, fov, channel_name, z_level)
|
|
if image is not None:
|
|
image_set.add(image)
|
|
yield image_set
|
|
|
|
@property
|
|
def height(self):
|
|
"""
|
|
:return: height of each image, in pixels
|
|
:rtype: int
|
|
|
|
"""
|
|
return self.metadata[six.b('ImageAttributes')][six.b('SLxImageAttributes')][six.b('uiHeight')]
|
|
|
|
@property
|
|
def width(self):
|
|
"""
|
|
:return: width of each image, in pixels
|
|
:rtype: int
|
|
|
|
"""
|
|
return self.metadata[six.b('ImageAttributes')][six.b('SLxImageAttributes')][six.b('uiWidth')]
|
|
|
|
def get_image(self, time_index, field_of_view, channel_name, z_level):
|
|
"""
|
|
Returns an Image if data exists for the given parameters, otherwise returns None. In general, you should avoid
|
|
using this method unless you're very familiar with the structure of ND2 files.
|
|
|
|
:param time_index: the frame number
|
|
:type time_index: int
|
|
:param field_of_view: the label for the place in the XY-plane where this image was taken.
|
|
:type field_of_view: int
|
|
:param channel_name: the name of the color of this image
|
|
:type channel_name: str
|
|
:param z_level: the label for the location in the Z-plane where this image was taken.
|
|
:type z_level: int
|
|
:rtype: nd2reader.model.Image() or None
|
|
|
|
"""
|
|
image_group_number = self._calculate_image_group_number(time_index, field_of_view, z_level)
|
|
try:
|
|
timestamp, raw_image_data = self._get_raw_image_data(image_group_number, self._channel_offset[channel_name])
|
|
image = Image(timestamp, raw_image_data, field_of_view, channel_name, z_level, self.height, self.width)
|
|
except TypeError:
|
|
return None
|
|
else:
|
|
return image
|